Choose one answer. In deep neural networks, the vanishing gradient problem occurs because Select one: a. the gradient of the sigmoid is close to zero in the saturated regions. b. the error term of neurons close to the output is computed by multiplying the gradient several times. c. the error term of neurons close to the input is computed by multiplying the gradient several times. d. a and b e. a and c f. b and c

Q: Which of the following statements are usually true about the Learning rate in Neural Networks? (1)…

A: If the learning rate is set too low, the weight change may be so large that the optimization may…

Q: l neural networks we use activation functions. Explain why you would select on activation function…

A: What are activation functions? To answer the question of what Activation Functions are, let’s first…

Q: Training neural networks requires two steps. In the forward pass we compute the output of the…

A: Arrow_forward.   Forward pass

Q: Four different machine learning algorithms are shown in this section, which may be used for…

A: ML algorithms: If the training data is huge and the number of observations is more than the number…

Q: Please provide a rationale for the selection of a specific machine learning model and its potential…

A: Selection of Machine Learning Models Machine learning models are tools that help us interpret,…

Q: Four different machine learning algorithms are shown in this section, which may be used for…

A: various machine learning techniques The amount of training data is: We may use low bias algorithms…

Q: Know how a backpropagation algorithm can be applied to updating the weights of a neural network

A: The backpropagation algorithm is used to train the neural networks by adjusting the weights of the…

Q: Given the neural network below, calculate and show the weight changes that would be made by one step…

A: Given the value, x1= 0.05 and x2=0.1 w1=0.15 , w2=0.2, w3=0.25, and w4=0.3. b1=0.35 and b2=0.6.…

Q: (please note that sometimes we use the symbol { instead of c) What are the new values of the vector…

A: You may build the truth table, view the values, and select the gate that the network imitates. 0 0 0…

Q: Consider the following procedure for initializing the parameters of a neural network: 1. Pick a…

A: Answer:  The correct option is (a) = No because the procedure fails to break the symmetry.

Q: using matlab 1. Plot the following functions on the same graph for x values from −2π to 2π,…

A: According to the information given:- We have to follow the instruction in order to get desired…

Q: How do I understand that I am getting the correct output when using the sigmoid function in a neural…

A: “Since you have asked multiple questions, we will solve the first question for you. If you want any…

Q: Consider a neuron with 2 inputs, 1 output, and a threshold activation function. If the two weights…

A: ANSWER :  GIVEN THAT :

Q: Seeing a row of stars written in black as part of the regular Stroop task would be modeled in…

A: The Cohen–Grossberg neural network model is considered, which includes both time-varying and…

Use of XOR function

XOR function or exclusive OR function was introduced in Excel 2013. This function is available under excel logical functions. For the given statement, the XOR function will return true only when either of the statements is true. It returns false when both the statements are true or when both the statements are false.